我的数据位于azure cosmos DB中，我已将数据集安装在azure databricks上。
我可以使用熊猫读取csv文件并将其加载到spark数据框。
df = pd.read_csv('/dbfs/mnt/ajviswan/forest_efficiency/2020-04-26_2020-05-26.csv')
sdf = spark.createDataFrame(df)
sdf.head()
这可以与以下输出到控制台一起使用，我可以对该数据框进行进一步处理。
(1) Spark Jobs
sdf:pyspark.sql.dataframe.DataFrame = [Forest: string, LoadBalanceMoveReason: string ... 4 more fields]
Out[34]: Row(Forest='AUSP282', LoadBalanceMoveReason='DefaultEncryption', CompletionDate='5/26/2020 12:00:00 AM', efficiencyRopCount=None, efficiencySize=0.9966470723725392, efficiencyIOPS=None)
但是，当我尝试直接使用spark数据帧读取文件时，它失败并显示读取错误。
df = spark.read.csv('/dbfs/mnt/ajviswan/forest_efficiency/2020-04-26_2020-05-26.csv')
df
返回
Py4JJavaError Traceback (most recent call last)
<command-4117735793908621> in <module>
----> 1 df = spark.read.csv('/dbfs/mnt/ajviswan/forest_efficiency/2020-04-26_2020-05-26.csv')
2 df
/databricks/spark/python/pyspark/sql/readwriter.py in csv(self, path, schema, sep, encoding, quote, escape, comment, header, inferSchema, ignoreLeadingWhiteSpace, ignoreTrailingWhiteSpace, nullValue, nanValue, positiveInf, negativeInf, dateFormat, timestampFormat, maxColumns, maxCharsPerColumn, maxMalformedLogPerPartition, mode, columnNameOfCorruptRecord, multiLine, charToEscapeQuoteEscaping, samplingRatio, enforceSchema, emptyValue, locale, lineSep, pathGlobFilter, recursiveFileLookup)
533 path = [path]
534 if type(path) == list:
--> 535 return self._df(self._jreader.csv(self._spark._sc._jvm.PythonUtils.toSeq(path)))
536 elif isinstance(path, RDD):
537 def func(iterator):
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
1303 answer = self.gateway_client.send_command(command)
1304 return_value = get_return_value(
-> 1305 answer, self.gateway_client, self.target_id, self.name)
1306
1307 for temp_arg in temp_args:
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
96 def deco(*a, **kw):
97 try:
---> 98 return f(*a, **kw)
99 except py4j.protocol.Py4JJavaError as e:
100 converted = convert_exception(e.java_exception)
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling o3781.csv.
: java.lang.NoClassDefFoundError: org/apache/spark/sql/sources/v2/ReadSupport
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(ClassLoader.java:756)
at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
at java.net.URLClassLoader.defineClass(URLClassLoader.java:468)
at java.net.URLClassLoader.access$100(URLClassLoader.java:74)
at java.net.URLClassLoader$1.run(URLClassLoader.java:369)
at java.net.URLClassLoader$1.run(URLClassLoader.java:363)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:362)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at com.databricks.backend.daemon.driver.ClassLoaders$LibraryClassLoader.loadClass(ClassLoaders.scala:151)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(ClassLoader.java:756)
at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
at java.net.URLClassLoader.defineClass(URLClassLoader.java:468)
at java.net.URLClassLoader.access$100(URLClassLoader.java:74)
at java.net.URLClassLoader$1.run(URLClassLoader.java:369)
at java.net.URLClassLoader$1.run(URLClassLoader.java:363)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:362)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at com.databricks.backend.daemon.driver.ClassLoaders$LibraryClassLoader.loadClass(ClassLoaders.scala:151)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at com.databricks.backend.daemon.driver.ClassLoaders$ReplWrappingClassLoader.loadClass(ClassLoaders.scala:65)
at java.lang.ClassLoader.loadClass(ClassLoader.java:405)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:370)
at java.util.ServiceLoader$LazyIterator.access$700(ServiceLoader.java:323)
at java.util.ServiceLoader$LazyIterator$2.run(ServiceLoader.java:407)
at java.security.AccessController.doPrivileged(Native Method)
at java.util.ServiceLoader$LazyIterator.next(ServiceLoader.java:409)
at java.util.ServiceLoader$1.next(ServiceLoader.java:480)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:44)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at scala.collection.IterableLike.foreach(IterableLike.scala:74)
at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
at scala.collection.TraversableLike.filterImpl(TraversableLike.scala:255)
at scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:249)
at scala.collection.AbstractTraversable.filterImpl(Traversable.scala:108)
at scala.collection.TraversableLike.filter(TraversableLike.scala:347)
at scala.collection.TraversableLike.filter$(TraversableLike.scala:347)
at scala.collection.AbstractTraversable.filter(Traversable.scala:108)
at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:696)
at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSourceV2(DataSource.scala:780)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:317)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:807)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
at py4j.Gateway.invoke(Gateway.java:295)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.ClassNotFoundException: org.apache.spark.sql.sources.v2.ReadSupport
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at com.databricks.backend.daemon.driver.ClassLoaders$LibraryClassLoader.loadClass(ClassLoaders.scala:151)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
答案 0 :(得分：1)
要从已挂载的存储中通过spark方法读取，则不应包含/dbfs前缀：
df = spark.read.csv('/mnt/ajviswan/forest_efficiency/2020-04-26_2020-05-26.csv')
答案 1 :(得分：0)
尝试以下一项，
df=spark.read.format("com.databricks.spark.csv").option("header", "true").option("inferschema", "true").option("mode", "DROPMALFORMED").load("/dbfs/mnt/ajviswan/forest_efficiency/2020-04-26_2020-05-26.csv")
df.show()
编辑＃1 老实说，我相信您的集群创建中存在一些配置问题。 如果您唯一的意图是读取COSMOS db数据。然后，您可以尝试以下操作，
readConfig = {
"Endpoint" : "https://<cosmos_end_point_name>.documents.azure.com:443/",
"Masterkey" : "<master_key_value>",
"Database" : "<database_name>",
"preferredRegions" : "East US",
"Collection": "<collection_name>",
"schema_samplesize" : "1000",
"query_pagesize" : "200000",
"query_custom" : "SELECT * FROM c"
}
df = spark.read.format("com.microsoft.azure.cosmosdb.spark").options(**readConfig).load()
为此，请在集群配置中的“ Maven软件包”下添加适用于Spark CosmosDB的Maven库。假设您的环境兼容，然后尝试使用'com.microsoft.azure:azure-cosmosdb-spark_2.4.0_2.11:3.0.2'